Biology subjects

Bi, Y.

Publications and source records attributed to Bi, Y..

At least 19 recordsLinked to original sources

bioRxiv2026

Charting sex divergence in the human brain across the lifespan

Biological sex fundamentally shapes human brain organization, but sex-specific normative neuroanatomical trajectories across the lifespan remain largely uncharted. Here, we constructed independent, sex-specific lifespan brain charts using structural neuroimaging data from 59,915 healthy individuals (29,760 males and 30,155 females) ranging in age from 266 postconception days to 100 years. By examining 296 structural phenotypes across global, cortical, and subcortical measures, these models revealed widespread sex differences in maturational timing, with males reaching peak milestones later than females. These trajectories demonstrate that sex differences evolve dynamically, with phenotype-specific windows of emergence and maximal separation. Compared with conventional sex-pooled references, sex-specific models achieved superior predictive accuracy and reduced misestimation of individual deviations in healthy populations. Across five neuropsychiatric conditions, sex-specific models improved the detection of extreme deviations and revealed both shared and sex-dependent patterns of disorder-related neuroanatomical abnormalities. These sex-specific charts establish tailored normative references for assessing brain development, ageing, and disease.

neuroscience↗

bioRxiv2026

LNP-CpG: deploy the self-adjuvant role of mRNA vaccines

With the rapid advancement of mRNA vaccines, lipid nanoparticles (LNPs) have emerged as pivotal carriers and adjuvants for non-mRNA vaccine modalities, driven by their superior nucleic acid delivery efficiency and intrinsic self-adjuvanting properties. In this study, we systematically evaluated various formulation strategies combining LNPs and the CpG adjuvant within a varicella-zoster virus glycoprotein E (VZV-gE) subunit vaccine framework. We demonstrated that uniform nanoparticles formed by LNP-encapsulated CpG (LNP-CpG), when simply admixed with the gE antigen, elicited superior immunogenicity compared to alternative encapsulation configurations. Intramuscular administration of a two-dose (LNP-CpG)+gE regimen significantly augmented both humoral and cellular immune responses in mice, markedly outperforming the commercial vaccine Shingrix (administered at a 1/10 human dose). Crucially, the identical regimen induced robust, comparable immune profiles to a full human dose of Shingrix in rhesus macaques. Furthermore, LNP-CpG displayed broad-spectrum utility across diverse vaccine platforms, demonstrating efficacy against both respiratory (RSV) and neurotropic (HSV) pathogens, compatibility with multiple modalities, including subunit (VZV-gE, RSV-Pre-F), live-attenuated (LA-HSV), and inactivated (i-HSV) vaccines; and versatile implementation in a combined VZV+RSV formulation. Collectively, our findings position LNP-CpG as a versatile, safe, highly efficacious adjuvant platform with substantial clinical translational potential, offering a compelling paradigm for next-generation vaccine development.

immunology↗

bioRxiv2026

Assessing Microcirculation Impairment in Ischemic Stroke Mice Using Arteriovenous Co-fluctuation Analysis

Accurate assessment of cerebral hemodynamics impairment traditionally relies on arterial metrics, yet often overlooks venous drainage and arteriovenous dynamics, thereby limiting the evaluation of ischemia-induced microvascular dysfunction. To address this limitation, we implemented a signal-averaging framework, combined with co-fluctuation analysis, to extract predominantly arterial and venous hemodynamic signals and construct a dynamic arteriovenous co-fluctuation index that quantifies frame-by-frame coordination between arterial inflow and venous outflow activity. This time-resolved index enables spatial characterization of large-scale cortical arteriovenous coordination beyond conventional static correlation-based analyses. Comparative analyses between healthy controls and acute ischemic stroke mice demonstrated that the arteriovenous co-fluctuation index sensitively detects disruption of vascular coordination, revealing a slower state transition that occurs alongside distinct temporal abnormalities and regional heterogeneity between ischemic core and penumbral regions. These findings underscore the utility of arteriovenous coordination as a sensitive indicator of microcirculatory dysfunction, offering a practical analytical tool for assessing stroke-induced microvascular impairment.

neuroscience↗

bioRxiv2026

Systematic Quantitative Proteomics Defines Age, Sex, and Region-Dependent Remodeling of Lung Extracellular Matrix

The lung extracellular matrix (ECM) governs tissue architecture, mechanics, and function, yet how it remodels with age across sex and anatomical regions remains poorly understood. Here, we performed a systematic multi-factor proteomic analysis of rat lungs to define age-, sex-, and region-dependent remodeling across the tissue landscape. Age emerged as the dominant source of variation, with a conserved aging signature modified by region- and sex-specific effects. Young lungs showed coordinated ECM assembly, balanced proteolysis, and active biosynthetic programs consistent with structural adaptability and mechanical resilience. In contrast, aged lungs exhibited accumulation of mature collagen crosslinks and a more stabilized matrix architecture, indicating progressive matrix maturation and reduced structural plasticity. These changes were accompanied by proteomic signatures of metabolic stress and immune activation, suggesting coordinated remodeling across ECM, metabolic, and immune pathways during lung aging. Aging effects varied across anatomical regions and were more pronounced in females, highlighting context-dependent trajectories within the broader aging program. Age also partially reshaped spatial proteomic heterogeneity across lung compartments. Together, these findings identify matrix stabilization as a central feature of lung aging that links structural remodeling to metabolic-inflammatory imbalance and increased pulmonary vulnerability.

biochemistry↗

bioRxiv2026

EEG-Neurofeedback Targeting Gamma Oscillations at the Parieto-Occipital Region Reduces Pain Perception

Pain is closely associated with both spontaneous and stimulus-evoked gamma oscillations, which differ in their phenomenology and their relationship to pain perception. These associations make gamma oscillations a promising target for pain interventions, such as closed-loop real-time neurofeedback (NFB). While modulating stimulus-evoked gamma oscillations is technically challenging due to their concurrent occurrence with pain perception, targeting spontaneous gamma oscillations is both feasible and practical, as it could influence subsequent cortical nociceptive processing and reduce pain. To test this mechanistic hypothesis, we developed a novel NFB training protocol aimed at increasing spontaneous gamma oscillations in the parieto-occipital region to alleviate pain. Eight-eight healthy, right-handed subjects were randomly assigned to either an active or sham NFB group and completed three sessions of NFB training. During each session, subjects underwent EEG recording and received randomized laser stimulation while watching a video. After three training sessions, approximately 52% of subjects in the active group successfully increased the spectral power of spontaneous gamma oscillations in the parieto-occipital region. Crucially, the spectral power of spontaneous gamma oscillations was significantly and negatively correlated with subjective pain intensity after the third NFB session. Additionally, subjects who responded successfully to active NFB showed significant reductions in pain intensity, unpleasantness, and laser-evoked potentials compared to the sham group. Together, these findings establish a causal relationship between spontaneous gamma oscillations in the parieto-occipital region and pain perception, potentially offering a novel NFB-based therapeutic strategy for pain management.

neuroscience↗

bioRxiv2026

Particle Biology: A Perspective on a First-Principles Theory of Life

This Perspective formally proposes Particle Biology as a unifying theoretical framework to address the critical bottleneck in current life science research. Current life science research has reached a critical bottleneck. While the field has advanced to the study of 3D genomic spatial configurations and chromosomal organization, it remains largely descriptive and confined to the macromolecular level. This approach lacks a first-principles understanding of the underlying physical forces that drive biological processes. This Perspective formally proposes Particle Biology as a unifying theoretical framework. We establish an axiomatic system positing that life phenomena are fundamentally emergent spatiotemporal patterns of electromagnetic forces among atoms, electrons, and nuclei operating far from thermodynamic equilibrium. By defining biological states through the Biological Hamiltonian and mapping biochemical pathways to multidimensional Potential Energy Surfaces (PES), we bridge the gap between descriptive biology and predictive physics. We categorize core research technologies into three modalities--seeing, computing, and controlling particles--facilitated by advancements in Cryo-EM, AlphaFold 3, and Boron Neutron Capture Therapy (BNCT). Ultimately, the trajectory of molecular biology has evolved from cells to DNA and onto the 3D spatial genome, yet it cannot go deeper within current paradigms. The next logical evolution is to move beyond the macromolecular bottleneck to focus on the electromagnetic interactions between atoms and ions--the true Particle Biology level--to redefine disease and intervention.

biophysics↗

bioRxiv2026

Linking sugar sensing to immunity in plants via O-glycosylation

Interaction with microbes can reprogram metabolism and alter nutrient availability in plant cells. How metabolic changes modulate immune responses remains unknown. Here, we show that sugar-sensing O-glycosylation of immune-signaling kinases mediates metabolic regulation of immunity. Under sugar-replete conditions, the MAP kinase kinases (MKK4 and MKK5), key components of pattern-triggered immunity (PTI), are glycosylated with O-GlcNAc and O-fucose on their activation loops, blocking their phosphorylation by upstream kinases and thereby restricting PTI. Pathogen infection or sugar starvation reduces O-glycosylation of MKK4/5 and enhances immune signaling; these effects are reversed by GDP-fucose treatment, demonstrating that reduced sugar availability decreases O-fucosylation and enhances immune signaling in infected cells. Chemical inhibition of O-fucosylation enhances immunity and pathogen resistance in both Arabidopsis and tomato. Our findings establish O-glycosylation of MKKs as a metabolic rheostat that fine-tunes immune responses according to sugar availability during plant-microbe interactions, providing a new strategy for improving crop health.

plant biology↗

bioRxiv2026

A residual-ratio framework for auditing transcriptomic gene signatures against background expression structure

BackgroundTranscriptomic gene signatures are widely used to infer pathway activity and biological mechanism from bulk cancer expression data, yet current evaluation strategies primarily emphasize internal coherence, predictive performance, or scoring robustness. A quantitative framework for assessing how much signature variation remains independent of background expression structure has been lacking. ResultsUnlike existing single-number signature-quality metrics such as Berglund uniqueness, residual-ratio auditing reports a trajectory across null-model richness: for each signature we compute the residual ratio [Formula] at progressively enriched expression-PC subspaces, together with an inverse-participation-ratio (IPR) concentration diagnostic that reports the effective number of axes absorbing each signature. Applied to a curated 17-entry benchmark, all 50 MSigDB Hallmark gene sets, and 1,181 Reactome pathways across 8 TCGA cancer types (4,462 samples), with external validation in METABRIC, the framework produces two complementary readouts. First, the curated panel is absorbed into the ExprPC50 subspace at residual ratios 18-43% below size-matched random 30-gene baselines in every cancer (curated mean r{perp} range 0.109-0.177 vs. random mean 0.182-0.288), providing the frameworks central quantitative discrimination between biologically coherent signatures and arbitrary gene combinations. Second, within the curated panel the ExprPC50 residual ratio is negatively correlated with the top-5 absorption concentration in every cancer (Spearman{rho} from -0.59 in PRAD to -0.89 in SKCM, median -0.71; all 8 significant at p < 0.05, most at p < 10-3); we report this correlation as a descriptive geometric property of the null-model coordinate system rather than as a biological law, because 1,000 random 30-gene draws projected through the same top-50 expression-PC basis reproduce the same pan-cancer median{rho} (-0.73; Supplementary Table S16), and it is robust to compositional nuisance: after rebuilding the null basis as immune-PC1 {oplus} stromal-PC1 {oplus} proliferation-PC1 plus 47 residual PCs, the per-cancer{rho} becomes more negative rather than shallower (median -0.86; Supplementary Table S17), ruling out tumor purity, immune infiltrate, and stromal fraction as drivers of the pattern. Because absorption at ExprPC50 is a geometric property of how any signature direction sits in expression-PC space, tier-level distributional structure at this operating point is not separable beyond the low-vs-upper band split: a Kruskal-Wallis omnibus is significant (p = 4.9 x 10-13), but pairwise Dunns post-hoc tests show that Tiers 1, 4, and 5 are not separable (pBH > 0.2). The trajectory shape itself is empirically bootstrap-invariant: across 200 sample-level fixed-basis bootstrap resamples of the 17 curated entries in BRCA, the mean pairwise Pearson correlation of trajectory-shape vectors is 0.999, and individual cell-level 95% bootstrap CI half-widths at B= 1,000 resamples are in the range 0.002-0.053. External replication in the METABRIC breast cancer cohort (nsamples = 1,980, microarray) showed moderate-to-strong rank-ordering concordance with TCGA-BRCA across the 17 curated entries (Spearman{rho} = 0.72 on the 17-signature ordering, 95% Fisher-z CI 0.37-0.89, p = 0.001). Under an upper-bound sensitivity analysis, 45 of 50 Hallmark gene sets and 992 of 1,181 Reactome pathways had ExprPC200 residual ratios below the mean of their size-matched random baselines--a descriptive statistic reflecting axis alignment under rich null models, not a failure rate. In causal DAG simulations (nrep = 100 replicates), a signature driven entirely by a latent confounder retained r{perp} = 0.233 at ExprPC50, numerically comparable to Tier 1 validated drivers, so a single-point residual ratio cannot adjudicate confounder-independence. The frameworks load-bearing signals are therefore the trajectory shape (statistically invariant under sample-level resampling) and the magnitude gap between the curated panel and its random 30-gene baseline (the curated-vs-random discrimination), read jointly--not the value of r{perp} at any single null-model dimensionality. O_TBL View this table: org.highwire.dtl.DTLVardef@1b56848org.highwire.dtl.DTLVardef@d18636org.highwire.dtl.DTLVardef@1c26db4org.highwire.dtl.DTLVardef@1b0620corg.highwire.dtl.DTLVardef@f507d2_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable S16:C_FLOATNO O_TABLECAPTIONRandom-gene-set null for the ExprPC50 r{perp}-vs-c(5) correlation, and curated-panel absolute gap vs random baselines. For each of the 8 primary-analysis TCGA cancer cohorts, we drew B = 1,000 random 30-gene sets from the gene universe of the preprocessed expression matrix and computed, for each draw, the residual ratio r{perp}(k = 50) and the top-5 absorption concentration c(5) under the same top-50 sample-space PC basis used for the curated benchmark (Methods [§]Statistical analysis; reference implementation accompanies the project repository as script 35). Column "Empirical curated{rho} " repeats the 17-signature Spearman{rho} between r{perp} and c(5) reported in the main text and in Supplementary Table S10; column "Null-A{rho} (random 30-gene)" gives the Spearman{rho} across the 1,000 random-draw (r{perp}, c(5)) pairs per cancer; column "{Delta} (emp null-A)" reports the difference. For reference, column "Null-B{rho} " gives the corresponding Spearman{rho} across 1,000 iid Gaussian unit vectors h (0, IN) in sample space (a uniform random direction that does not inherit the expression covariance geometry). Rightmost columns compare the curated 17-entry panels mean r{perp} at ExprPC50 to the random 30-gene baseline mean, both in absolute units and as a percentage gap; this magnitude gap is the quantitative discrimination between curated biological signatures and arbitrary gene combinations on which the frameworks central claim rests. C_TABLECAPTION C_TBL O_TBL View this table: org.highwire.dtl.DTLVardef@d4a1d3org.highwire.dtl.DTLVardef@1cc3baaorg.highwire.dtl.DTLVardef@1611aecorg.highwire.dtl.DTLVardef@2e9c76org.highwire.dtl.DTLVardef@220711_HPS_FORMAT_FIGEXP M_TBL O_FLOATNOTable S17:C_FLOATNO O_TABLECAPTIONPurity-aware null for the curated-panel ExprPC50 r{perp}-vs-c(5) correlation. For each cancer we rebuild a rank-50 sample-space basis as follows. Columns 1-3 are the PC1 directions of: an immune-infiltrate proxy panel (CD3D, CD3E, CD4, CD8A, CD8B, CD19, CD68, PTPRC, FOXP3, IFNG); a stromal/fibroblast proxy panel (COL1A1, COL1A2, COL3A1, VIM, FN1, ACTA2, PDGFRA, PDGFRB); and the 50 proliferation markers already used in the null-model hierarchy ([§]Null model hierarchy). Columns 4-50 are the top-47 PCs of the residual expression matrix Y - QbioQ Y after QR-orthonormalization of the 3-column biological block; the full 50-column basis is re-orthonormalized by a final QR pass. The 17 curated benchmark entries are then re-scored under this purity-aware basis, and the per-cancer Spearman{rho} between r{perp} and c(5) is recomputed. Column "Standard{rho} " is the value reported in the main text (same as Supplementary Table S16, column "Empirical curated"); column "Purity-adjusted{rho} " is the value under the new basis; column "{Delta}" is the difference. This test was pre-specified as a check on whether the observed{rho} (r{perp}, c(5)) could be driven by tumor-purity, immune, or stromal composition artifacts that a standard top-50 PC basis would implicitly absorb. C_TABLECAPTION C_TBL ConclusionsResidual-ratio auditing provides an interpretable and practical framework for quantifying how much of a transcriptomic gene signatures variance remains orthogonal to a chosen background-expression model. The two statistically reliable quantities it reports are (i) the shape of the trajectory r{perp}(k) across null-model richness, which is bootstrap-invariant across sample-level resamples, and (ii) the magnitude gap between the curated panels residual ratio and size-matched random 30-gene baselines at a fixed operating point, which is 18-43% in all 8 TCGA cancers and survives a purity-aware null-model construction. The negative correlation between r{perp} and the top-5 absorption concentration c (curated-panel median{rho} = -0.71) is reproduced by random 30-gene sets under the same basis (random-draw median{rho} = -0.73) and is therefore best read as a descriptive geometric property of the null-model coordinate system rather than a biological discovery about curated signatures. Any single operating-point residual ratio carries materially wider cell-level uncertainty than the trajectory shape and cannot, on its own, adjudicate confounder-independence. The frameworks outputs describe a signatures geometric relationship to modeled background expression structure and do not evaluate clinical utility: a signature with a low residual ratio may still be clinically valuable when that low value reflects alignment with a strong prognostic or actionable program such as proliferation, immune infiltration, or cell cycle, and the framework is not a substitute for calibrated prognostic or predictive classifiers. All findings are based on bulk RNA-seq (TCGA PanCancer Atlas, 8 cancer types) and microarray (METABRIC) data; transfer to single-cell, single-nucleus, or spatial transcriptomics is out of scope and not claimed. Used within this scope--reading the trajectory shape and the magnitude-gap signal jointly, rather than the value of r{perp} at any one k--the framework adds a complementary audit layer to existing pathway-scoring and experimental-validation workflows, and supports more calibrated interpretation, comparison, and reporting of transcriptomic gene signatures in cancer studies.

bioinformatics↗

bioRxiv2026

Structure-aware geometric graph learning for modeling protease-substrate specificity at scale

Protease-substrate specificity is central to cellular regulation and disease pathogenesis, and accurately modeling its structural determinants remains challenging. Substrate recognition is governed by spatial constraints and higher-order relationships that extend beyond local sequence motifs. Most computational approaches rely predominantly on motif-centric or sequence-based representations, limiting their ability to capture the geometric and relational structure underlying enzymatic specificity. Here, we introduce OmniCleave, a structure-aware geometric graph learning framework for modeling protease-substrate specificity at scale. OmniCleave is trained on 57,278 structure-informed protease-substrate pairs derived from 9,651 substrates spanning over 100 proteases across six distinct families. The framework integrates multi-scale structural graphs with higher-order protease relational topology, explicitly encoding spatial context and inter-protease dependencies within a unified geometric representation. This formulation moves beyond local pattern recognition and enables transferable modelling across six protease families. Across large-scale benchmarks, the framework consistently outperforms existing approaches and reveals interpretable geometric determinants underlying substrate recognition. Experimental validation confirms three novel caspase-3 substrates and 21 cleavage sites predicted by OmniCleave, supporting the biological relevance of the learned representations. Together, OmniCleave provides a scalable geometric framework for modeling protease-substrate specificity, with practical utility for systematic analysis of protease biology.

bioinformatics↗

bioRxiv2026

Spectral Graph Features for Reference-free RNA 3D Quality Assessment

MotivationExisting RNA 3D structure quality assessment (QA) methods rely on local geometric descriptors or statistical potentials that evaluate atomic-level contacts but are blind to global topological coherence. This creates a critical failure mode--structures that are "locally correct but globally wrong"--where well-formed local helices mask misplaced domains and incorrect overall packing. ResultsWe introduce SpecRNA-QA, a lightweight RNA QA method based on multi-scale graph-Laplacian features of inter-nucleotide contact networks. In CASP16 leave-one-out cross-validation, it achieves median per-target Spearman{rho} = 0.69 (target-clustered bootstrap 95% CI [0.64, 0.73]) versus 0.47 for an internal geometry baseline--a +0.22 gap that is significant at p = 1.2 x 10-10 (one-sided Wilcoxon signed-rank) and reflects a per-target win rate of 93%. The gain is concentrated on large, multi-domain RNAs, where global coherence is poorly captured by local descriptors. In a contextual comparison with established statistical potentials, local energy-based scores remain strongest on compact RNAs, while SpecRNA-QA yields the strongest signal we observed on targets longer than 200 nt; within the single-threaded runtime budget used here, the strongest local-energy comparator, rsRNASP, timed out on 22 of 26 large targets, and we report an explicit paired head-to-head on the four commonly scored targets in Section 4.2. A training-free heuristic variant further shows that the spectral prior carries intrinsic quality information even in the absence of labeled QA data. AvailabilitySpecRNA-QA is available as a Python package at https://github.com/yudabitrends/specrnaq. Contactybi3@gsu.edu Supplementary informationSupplementary data are available online. Key PointsO_LISpecRNA-QA uses multi-scale graph-Laplacian spectra to score global RNA fold coherence that local geometric descriptors and local statistical potentials can miss. C_LIO_LIThe method uncovers a size-dependent division of labor: on compact RNAs that can be scored exhaustively, atom-level statistical potentials such as rsRNASP remain strongest, whereas on >200 nt RNAs--where the strongest local comparator times out on most targets under the single-threaded runtime budget used here--SpecRNA-QA provides the strongest signal we observed. C_LIO_LIHeat-kernel traces at intermediate diffusion times emerge as the most discriminative spectral features and form an interpretable bridge between local packing and long-range tertiary organization. C_LIO_LIA training-free heuristic variant of SpecRNA-QA retains informative spectral signal without any labeled QA data, supporting the interpretation of the learned model as amplifying a real structural signal rather than overfitting one. C_LI

bioinformatics↗

bioRxiv2026

Xylulose 5-Phosphate/Phosphate Translocator Mediates Carbon Allocation for Anabolic Metabolism in the Chlamydomonas Chloroplast

Metabolite movement into chloroplasts is essential for sustaining chloroplast anabolic metabolism and cellular growth, and yet how the specific factors/transporters that enable import and support metabolism under heterotrophic conditions (in the dark in the presence of fixed carbon) remain poorly understood. Here, we identify CreTPT10, a chloroplast envelope-localized transporter in the unicellular green alga Chlamydomonas reinhardtii (Chlamydomonas throughout) that, of the substrates tested, has the highest specificity for xylulose 5-phosphate (X5P). We also demonstrated that the loss of CreTPT10 caused a pronounced reduction in growth and respiratory activity in the dark, whereas no growth defects were observed in the tpt10 mutants when they were maintained in the light or under nutrient-limiting conditions. Furthermore, dark-grown tpt10 mutants exhibited markedly reduced levels of lipids, nucleotides, isoprenoids, and aromatic secondary metabolites, accompanied by coordinated repression of genes encoding enzymes associated with chloroplast-localized biosynthetic pathways. This metabolic suppression extended beyond the chloroplast, as genes associated with the mitochondrial respiratory chain and cell cycle progression were markedly downregulated in darkness. Together, these findings indicate that X5P import via CreTPT10 is critical for sustaining chloroplast anabolic metabolism and functionally coordinates chloroplast and mitochondrial energy metabolism to support heterotrophic growth.

plant biology↗

bioRxiv2026

Graph-based RNA structural representation reveals determinants of subcellular localization

RNA subcellular localization is a key determinant of RNA function and regulation, yet existing computational approaches rely primarily on sequence or simplified structural descriptors, limiting their scalability to long transcripts, their ability to model inter-label dependencies, and their applicability across RNA types. Here, we present GRASP, a unified graph neural network framework for predicting RNA subcellular localization using a heterogeneous graph representation that is RNA substructure-aware. GRASP presents each RNA as a multi-scale graph comprising nucleotide nodes and secondary-structure-derived substructure nodes, connected by relational edges, enabling joint modeling of base-level interactions and regional structural context. The model further incorporates multi-label dependency learning to capture co-localization patterns across cellular compartments within a unified framework. Across multiple benchmark datasets and RNA types, GRASP consistently outperforms state-of-the-art sequence-based and structure-informed methods, achieving substantial improvements in accuracy, F1 score, and AUC while maintaining strong scalability to long transcripts. In addition, the graph-based representation provides biologically interpretable insights into structural determinants of RNA localization. The source code and data are available at https://github.com/ABILiLab/GRASP, and the web server is accessible at http://grasp.biotools.bio.

bioinformatics↗

bioRxiv2026

Causal evidence for a shared mechanism linking language and tool use via the putamen

Both human language and tool use--two hallmark capacities of human cognition--depend on organizing discrete elements, i.e., symbols and actions, into highly constrained structured sequences to achieve a functional goal. However, the neural mechanism linking these capacities is unclear. We combined brain lesion analysis, developmental contrast, and functional neuroimaging to test whether the basal ganglia play a causal role in their shared capacity. In 100 adults with focal brain injury, damage to the putamen disrupted both sentence processing and tool use, with impairments specifically explained by reduced goal-dependent sequence integrity for both tasks. Further comparing populations with typical and deprived early language experience (congenitally deaf adults with vs. without early sign language exposure), we found that early language acquisition was associated with improved tool-use performance and strengthened putaminal responses to such goal dependency, which mediated the relationship between sentence sequence integrity and tool behavior. Together, these results identify the putamen as a key neural substrate supporting goal-dependent sequence integrity across language and action, and show how early language experience shapes this conserved control system. One-Sentence SummaryLanguage and tool use share a putamen-based mechanism that supports goal-dependent sequence integrity, and this mechanism is strengthened by early language experience.

neuroscience↗

bioRxiv2025

Prognosis prediction using autophagy gene expression in osteosarcoma

Defining the transition from localized to metastatic osteosarcoma (OS) before overt dissemination is fundamental for improving survival. However, effective early diagnostic tools remain scarce, largely due to limited exploitation of the pre-metastatic tumor microenvironments own record of molecular barcode exposures encoded in cell-intrinsic stress states. We analyzed autophagy-dependent transcriptional datasets from 139 individuals to develop Auto-RS, a computational classifier that can integrate age and sex to deliver individualized risk management. The prognosis-interpretable features of Auto-RS recapitulate established molecular trajectories of metastasis at the single-cell level, capturing tumor cells intrinsic shift from proliferative to invasive states and revealing cooperative programs among cancer-associated fibroblasts and immune cells. More significantly, Auto-RS can expose chemotherapy vulnerabilities of newer drugs, providing a framework to prioritize therapeutics without direct testing in children. This framework brings a potential inflection point, where metastasis prediction and therapeutic stratification may converge to improve OS outcomes.

cell biology↗

bioRxiv2025

MORC2 Mediates Transcriptional Regulation Through Liquid-Liquid Phase Separation and DNA Binding

MORC2 is a chromatin-associated ATPase essential for transcriptional silencing and genome stability, yet the biophysical principles governing its regulatory activity remain elusive. Here, we demonstrate that full-length MORC2 undergoes biomolecular condensation to form dynamic nuclear assemblies, a process fundamentally required for its repressor function. Endogenous MORC2 forms discrete, dynamic condensates in neurons from EGFP-MORC2 knock-in mice, supporting the physiological relevance of these assemblies in vivo. Mechanistically, a 3.1 [A] crystal structure of coiled-coil 3 (CC3) identifies a dimeric scaffold that serves as a structural hub, while multivalent sticker interactions between an intrinsically disordered region (IDR) and a newly defined IDR-binding domain (IBD) drive condensation. We show that DNA acts as a molecular scaffold that triggers MORC2 condensation, which in turn allosterically stimulates its ATPase activity. Critically, by employing a "killswitch" strategy to decouple assembly from internal fluidity, we reveal that only dynamic MORC2 condensates--not static aggregates or condensation-deficient mutants--can restore transcriptional repression in MORC2-knockout cells. Furthermore, pathogenic variants linked to CMT2Z and SMA differentially perturb these material properties and enzymatic turnover, providing a mechanistic link between condensate dysregulation and human neuropathies. Together, our findings establish a DNA-templated condensation mechanism for MORC2 and provide a molecular framework for understanding how the material state of chromatin-associated machinery dictates gene regulation and disease pathogenesis

cell biology↗

bioRxiv2025

A tale of three types of internal object representations in the human brain

Perception and mental imagery are widely thought to rely on overlapping neural representations, giving rise to perception-like visual experiences during imagery generation. However, such overlap, by itself, is agnostic to the nature of the underlying neural geometry for both perception and imagery. Here we addressed this question by comparing visualizers and individuals with congenital aphantasia using fMRI, representational similarity analysis, and multimodal deep neural network models to probe different types of neural geometry. Despite comparable behavioral performance and perception-imagery generalization of neural object representations in the ventral occipitotemporal cortex, the two groups exhibited systematically different object representational geometries already in the perceptual encoding phase. Visual-similarity-aligned geometry was selectively reduced in the left lateral occipitotemporal cortex of individuals with aphantasia during perceptual encoding, before imagery generation, and its expression during imagery covaried with imagery vividness. In contrast, language-relation-aligned geometry was preserved across groups during both perception and imagery. Together, these findings suggest that subjective imagery experience is associated with the geometry of neural object representations during both perception and imagery, and that representations within perception- imagery cross-decoding regions comprise heterogeneous components rather than a unitary shared neural code.

neuroscience↗

bioRxiv2025

The Winners Take It All? Evolutionary Success ofH5Nx Reassortants in the 2020-2024 Panzootic

Avian influenza viruses undergo frequent genetic reassortment, which can coincide with phenotypic changes in transmission, pathogenicity, and host species niche. Since 2020, clade 2.3.4.4b H5 high pathogenicity avian influenza viruses (HPAIVs) have driven a global panzootic, causing mass mortality in wild birds, poultry, and, for the first time, repeated spillover infections in a variety of mammalian species. This worldwide resurgence of H5 HPAIV has coincided with a dramatic increase in the number of circulating reassortant strains; however, the scale, impact and drivers of these reassortants remain unclear. Here, we combined statistical and phylodynamic modelling to reconstruct the global evolutionary dynamics of H5Nx viruses across four epizootic seasons (2020-2024). We identified 209 genetically distinct reassortants, stratified into three transmission categories based on their phylogenetic and epidemiological profiles. Accounting for sampling depth and HPAIV incidence, we estimated that reassortants emerged most frequently from Asia, but major reassortants associated with increased host range, inter-seasonal persistence, and long-range dissemination, more frequently emerged from Europe. Altogether, reassortant emergence followed an episodic pattern in which most reassortants were transient, but 2% seeded large clusters of secondary reassortants soon after their own emergence. Statistical modelling revealed that reassortant success was strongly shaped by ecological factors, including sustained circulation in specific wild bird orders and detection across a wider range of host niches. Collectively, our findings uncover global reassortment dynamics in H5 HPAIVs and identify key virological and ecological drivers underpinning the emergence and spread of successful reassortants. These insights support the importance of enhanced surveillance to track evolution of H5 HPAIV and identify traits relevant for consideration in pandemic risk assessment.

evolutionary biology↗

bioRxiv2025

Isoliensinine Ameliorates Pathological Cardiac Hypertrophy After Aerobic Exercise by Activating Cytochrome c Oxidase Subunit 6A2

Pathological cardiac hypertrophy is an abnormal remodeling process of the heart under chronic pressure overload, characterized by myocardial fibrosis, apoptosis, and progressive decline in cardiac function, ultimately leading to heart failure or death. Although aerobic exercise, particularly swimming, has been shown to alleviate pathological cardiac hypertrophy, its molecular mechanisms remain incompletely understood. In this study, metabolomic and transcriptomic analyses revealed the molecular mechanisms underlying swimming-induced improvement of pathological cardiac hypertrophy. Results showed that swimming training significantly altered the level of isoliensinine in animals. Further studies demonstrated that isoliensinine exerts cardioprotective effects by regulating the expression of Cytochrome C Oxidase Subunit 6A2 (COX6A2), establishing for the first time the critical role of the Isoliensinine-COX6A2 signaling axis in cardiac function regulation. To validate this axis, a pathological cardiac hypertrophy model was constructed in mice through transverse aortic constriction (TAC). Both swimming training and isoliensinine intervention significantly improved cardiac structure and function. In vitro experiments using isoproterenol (ISO)-induced hypertrophy in H9C2 cells further confirmed the essential role of this signaling axis in suppressing pathological hypertrophy and maintaining mitochondrial homeostasis. Our findings demonstrate that swimming mitigates pathological cardiac hypertrophy by enhancing COX6A2 expression by isoliensinine, thereby improving mitochondrial function. This study not only expands the understanding of exercise-mediated mechanisms in pathological cardiac remodeling but also highlights the cardioprotective potential of isoliensinine and COX6A2 as therapeutic targets for preventing and treating heart failure.

molecular biology↗